Medical imaging, including X-ray, magnetic resonance (MR), computed tomography (CT), ultrasound, and various combinations of these and other image acquisition modalities are utilized to provide images of internal patient structure for diagnostic purposes as well as for interventional procedures. Often, it is desirable to utilize multiple two-dimensional (i.e. 2-D) images to generate (e.g., reconstruct) a three-dimensional (i.e., 3-D) image of an internal structure of interest.
2-D image to 3-D image reconstruction has been used for a number of image acquisition modalities (such as MRI, CT, Ultrasound) and image based/guided procedures. These images may be acquired as a number of parallel 2-D image slices/planes or rotational slices/planes, which are then combined together to reconstruct a 3-D image volume. Generally, the movement of the imaging device has to be constrained such that only a single degree of freedom is allowed (e.g., rotation). This single degree of freedom may be rotation of the equipment or a linear motion. During such a procedure, the presence any other type of movement will typically cause the registration of 2-D images in 3-D space to be inaccurate. This presents some difficulties in handheld image acquisition where rigidly constraining movement of an imaging device to a single degree of freedom is difficult if not impossible. Further constraining an imaging device to a single degree of freedom may also limit the image information that may be acquired. This is true for handheld, automated and semi-automated image acquisition. Depending upon the constraints of the image acquisition methods, this may limit use or functionality the acquisition system for 3-D image generation.
Many 3-D reconstruction techniques currently require a significant number of 2-D images in order to achieve a reasonably good resolution. This typically results in a slow scan process and/or slow 3-D image reconstruction. The requirement of a large number of 2-D images may also lead to unnecessary workflow issues, causing hindrance to workflow and/or patient discomfort. Further, in many imaging situations, the actual region of interest is generally much smaller than the actual image acquired, resulting in unnecessary computational overheads for interpolation at regions outside the object of interest. During a medical procedure such as image based biopsy or therapy, a user is generally interested in only one organ and not in the background information. Further, in operating room environments time allocated for imaging procedures and/or image guide procedures is minimal due to time pressures on surgeons to undergo more procedures in allocated time. Accordingly, it is desirable to perform 3-D image generation in a manner that reduces the constraints on image acquisition and allows for quickly generating a 3-D image, while also providing sufficient resolution to perform a desired procedure.